For infrared focal plane graded during signal acquisition array sensors, imagery is departicularly nonuniformity. In this paper, an adaptive nonuniformity correction technique is proposed which simultaneously estimate...For infrared focal plane graded during signal acquisition array sensors, imagery is departicularly nonuniformity. In this paper, an adaptive nonuniformity correction technique is proposed which simultaneously estimates detector-level and readout- channel-level correction parameters using neural network approaches. Firstly, an improved neural network framework is designed to compute the desired output. Secondly, an adaptive learning rate rule is used in the gain and offset parameter estimation process. Experimental results show the proposed algorithm can achieve a faster convergence speed and better stability, remove nonuniformity and track parameters drift effectively, and present a good adaptability to scene changes and nonuniformity conditions.展开更多
The striping pattern nonuniformity of the infrared line scanner （IRLS） severely limits the system performance. An adaptive nonuniformity correction （NUC） algorithm for IRLS using neural network is proposed. It use...The striping pattern nonuniformity of the infrared line scanner （IRLS） severely limits the system performance. An adaptive nonuniformity correction （NUC） algorithm for IRLS using neural network is proposed. It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that the algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.展开更多
We present a robust and fiducial-marker-free algorithm that can identify and correct stick-slip distortion caused by nonuniform rotation(or beam scanning)in distally scanned catheters for endoscopic optical coherence ...We present a robust and fiducial-marker-free algorithm that can identify and correct stick-slip distortion caused by nonuniform rotation(or beam scanning)in distally scanned catheters for endoscopic optical coherence tomography(OCT)images.This algorithm employs spatial fre-quency analysis to select and remove distortions.We demonstrate the feasibility of this algorithm on images acquired from ex vivo rat colon with a distally scanned DC motor-based endoscope.The proposed algorithm can be applied to general endoscopic OCT images for correcting non-uniform rotation distortion.展开更多
基金supported by the National Natural Science Foundation of China (61101199)the Natural Science Foundation of Jiangsu Province (K2011699)the Colleges and Universities Innovation Projects (CX08B 045Z)
文摘For infrared focal plane graded during signal acquisition array sensors, imagery is departicularly nonuniformity. In this paper, an adaptive nonuniformity correction technique is proposed which simultaneously estimates detector-level and readout- channel-level correction parameters using neural network approaches. Firstly, an improved neural network framework is designed to compute the desired output. Secondly, an adaptive learning rate rule is used in the gain and offset parameter estimation process. Experimental results show the proposed algorithm can achieve a faster convergence speed and better stability, remove nonuniformity and track parameters drift effectively, and present a good adaptability to scene changes and nonuniformity conditions.
基金This work was supported by the Pre-Research Foundation of National Defense under Grant No. 30404.
文摘The striping pattern nonuniformity of the infrared line scanner （IRLS） severely limits the system performance. An adaptive nonuniformity correction （NUC） algorithm for IRLS using neural network is proposed. It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that the algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.
基金supported in part by the National Institutes of Health under the grant No.R01 HL121788The Wallace H.Coulter FoundationMaryland Innovation Initiative(MII)Fund from TEDCO
文摘We present a robust and fiducial-marker-free algorithm that can identify and correct stick-slip distortion caused by nonuniform rotation(or beam scanning)in distally scanned catheters for endoscopic optical coherence tomography(OCT)images.This algorithm employs spatial fre-quency analysis to select and remove distortions.We demonstrate the feasibility of this algorithm on images acquired from ex vivo rat colon with a distally scanned DC motor-based endoscope.The proposed algorithm can be applied to general endoscopic OCT images for correcting non-uniform rotation distortion.
